Nobody "Wants" AI (and other lessons from Henry Ford)

Well, Rob, welcome back, man.

We're here.

We, we have an announcement to make. We, we are actually two AI machines that like, we don't actually exist in, in real life. And this has all been like a, a spam.

Yeah. Yeah. Yeah. It is, uh, uh, unfortunately AI can now just ramble. And so it's taken both of our jobs.

Yeah. Yeah. That's right. The, we're, we're testing, uh, AI slop in, in podcast form and turns out it doesn't grow super fast.— like, you know, we moderate growth, like listener on multiple platforms, but not a whole lot more. We are talking about AI today though. So "Nobody Wants AI" is the, is the title of the Substack. This one's, this one's cool. And let's just get straight into the AI hype with this. But tell us what's on your, what's on your mind that this was the topic for the week.

Yeah. So basically I just see a lot of posts about it's the new requirement to go zero to $400 million ARR in about 14 seconds because of AI. And so what that does in me is it's like, uh, I need, like, uh, I need to understand why AI startups are growing super fast. And, uh, otherwise it's just kind of, not helpful to, to, to say that, like, I, I get it. I want to build a startup that grows super fast, but there's this sense that, okay, AI is totally changing some sort of game that's happening. What's actually working? Why are these AI startups growing so fast? What's actually happening here? And they get, there's, you know, the hype and then there's a lot of hate and I haven't. I've been thinking about this and like, how do we actually understand this? How do we explain this? And, and yeah, and so this is my attempt.

Yeah. And having, having read through the post and talked with you about AI for a long time, some of the background here is like you're, you're, you're not a Luddite. Like you're, you're very, you're actually very, you're very pro when there is demand that AI helps to meet. And so you work with a lot of AI startups. And so like nobody wants AI that you're not saying like Everybody should go back to a world of pre-ChatGPT. What you're saying is it's misunderstood why AI is causing some startups to take off. And you're hinting there at people are mistaking supply and demand.

Yes. Yeah, yeah, that's exactly it. Like I wrote the headline, the title, just to, I don't know, 'cause I thought it was kind of spicy. It is spicy. —what you, but yeah, what I see a lot of is that there's a bunch of people who, what, just think AI is a load of junk. It's a load of garbage and they're wrong, right? Like they're, they're just wrong. And I think the people who, but there are also people who are hyping it up and like focusing on the technology side and saying the technology is what's causing the startups to grow super fast who are also wrong. And so my, yeah, my, my sense is that that if we understand the mechanics of what causes startups to take off, what causes new technologies to take off, like generally, and then apply that to AI startups or just apply that to AI or apply that to whatever domain we are working in, we can build better companies and a better future. And I am a super bullish person on AI and on the future and on building awesome stuff. Like, yeah, that's what I'm about. I am very much against the kind of person who wants to go sit in the dark and turn back the clock on technology. I think that's like absolute nonsense and fundamentally misunderstands how the world works. And then I'm also against the kind of person who is like, you know, AI is like, I don't know, it's because of the transformer architecture that people want it now. It's like, no, no, no, that's, that's kind of missing the point here.

Yeah. Yeah. This is, I think this is a, it's great for, uh, us to be talking about AI given how relevant it is to the, the startups that work with you. And also just even for folks that may be watching who don't have AI businesses, AKA me, like we use it, we're not fundamental, like we're not designing an AI service or, or product. Um, it's a helpful way to understand or to think through what is supply and what is demand. 'Cause it, you really tease it out extremely clearly and very specifically in, in this one. Maybe before we jump into like really the post, who is this? Who is this for? Who is this most relevant for?

This is, this is a post for the homies. This is for everyone. This is, I think that if You understand this post, you understand something fundamental about how the world works, why startups take off, why, um, like why things have gotten better significantly since the Industrial Revolution and continuously like this, this is a means of understanding that and not necessarily predicting where the future will go. But understanding how the future is made.

Yeah, I love it. I love it. And you're— that part of the, the blog post, I highly recommend folks, folks, uh, pulling up and, and reading through. Um, it's a really interesting observation about the granular mechanics of, of progress, which was, I think, actually something you've been very interested in for a long time. It's like when somebody asks, like, what's the economy? It's like, Oof, good question. But because it's all, it's all coming at it from the other direction about like aggregate goods and you come at it from the opposite, which is what does, what does an entrepreneur do? Like what is a product? And then how does that grow into an economy or how does that sum basically into an economy? Anything to say on, on that, Rob? We'll probably get to that in a little bit.

Let's, we'll get to that. Let's, let's start with, we're gonna, we're gonna work our way to AI, but first we have to start Probably the number 2 question I get when somebody is starting to engage with my frameworks and like with the kind of the pull framework and the stuff that I write, which is the, but Henry Ford quote, the, which is, it's, you know, if I asked people what they wanted, they would've said faster horses. Yeah. Right. It, you know, I like, didn't look too hard into the quote. It's not clear that Henry Ford actually ever said that. I feel like that was somebody in the '90s who was like selling some sort of like services who was like, you know, but, and the quote just stuck. But I, but I don't, again, maybe he said it, maybe he didn't. It doesn't matter. We'd have to start with that quote because if you take that quote at face value, you will not understand why AI startups take off and you will not understand why the automobile took off.

Yeah, well, let's get it, let's get into it. I think this is, this is awesome. And it's, uh, I, this one important for a couple, it's, I think I'll use when we as founders want to be lazy, uh, essentially about demand. Um, uh, but why don't you using a supply and demand perspective, Rob, like take that on head on? Why is that a quote that you hate?

Yeah, so It is literally true. Like nobody would, like nobody would've said, I want an automobile before an automobile existed. And also it is an irrelevant quote because what it does is it conflates wanting supply with having demand. And so let's break these things apart. Demand for the automobile was, or like demand in the case of the automobile was like, I'm trying, I need the ability to get from point A to point B. That's what I'm trying to do. That demand is supply agnostic. It does not, it does not require me to say, right, I need an automobile, right? Or I want a train or I want a horse or whatever, whatever it is. Those things are supply side concepts. They are the, the things I use to, to like get to point B. So we have to separate demand, which is the thing I'm trying to do. That, that's what I want. I want the ability to get to point B. I don't want the thing on the supply side. The supply side is just How the means by which I get there, my demands for the ability to get to point B is what makes supply relevant. When I want to get to point B, when I want the ability to get to point B, I consider different options on the supply side and pick the one that fits best. When I do that, maybe I buy a horse, maybe I buy a car, like whatever it is. When I do that, that is, that looks like I want a car because I am buying one, but I don't actually want a car. I want the ability to get to point B. That is supply agnostic. So I'll pause there. Does that, did I explain that okay?

Yeah. I love the, I love the supply agnostic, uh, framing of this. It's like what exists pre-technology essentially, or, you know, in pre— if you ceased to exist, if Henry Ford had ceased to exist or never existed or had been an accountant that, you know, didn't do— yeah, I don't actually— was he an engineer? I'm not sure what Henry Ford was, but anyways, if he wouldn't have invented the automobile, would people still have needed to move from point A to point B. And then similarly, like applying to our, you know, to the listener can think about their startup. It's like what if they— if you had gone into— if you were a circus performer instead of an entrepreneur and you're the technology you're developing never existed, what would exist without you? What would exist in the customer's life without you? And that's one way of thinking through like what is demand in your situation.

Yeah. And I, I'd encourage reading through the couple of paragraphs here as well. Like the couple paragraphs in the newsletter, I like had to work to make very specific language so that it makes sense. Right. Yeah. And it's like, it's basically when we think, when we realize that supply and demand are different things and demand is what buyers actually want and it is supply agnostic. Then we can understand why products and technologies take off. If we don't understand that, we can't understand it. Like we, it just, we think that it's something about the product that causes people to want it. And that is a total misunderstanding. Yeah. Yeah.

Um, where, let's, before we get into AI specifically, You said this is like one of your FAQs basically, or people, the, the "but Henry Ford" objection that you get to your work. What is going on? Uh, why do people raise that with you? Like, what are they communicating?

Yeah. So, so it's, it's basically like, hey, I'm building something that is new. And so buyers don't want it. Like, it would be crazy if buyers wanted this new thing that we are building. Because it's a new category of things. And so we're like, don't we have to convince them to want it? Didn't Henry, like, didn't Henry Ford, da da da da da da, like, like, didn't Henry Ford do that? And that, that is kind of like misunderstanding two things. One, it's misunderstanding kind of like what you are looking for when you are observing customers and looking for demand. Mm. Because it's like, yeah, you, if you watch somebody, you're never going to see them wanting your new category of product. Yeah. What you're going to see is them doing stuff and you have to interpret like, okay, is there a space for a new product here that they will pull? Yeah. So it's one thing is like misunderstanding customer research. And the second point is just like, it's misunderstanding why people buy things at all and why certain products take off. Products take off because people have demand. They have things they are trying to accomplish in their lives and their existing options do not fit on the supply side. Right? The supply side does not fit the demand they have so that when you show up with a new thing, new category of thing, like something that's totally different and new and innovative, it has to fit demand. It has to fit what buyers are trying to accomplish better than their existing options. If that's the case, they will rip it out of your hands. And like, it may just so happen that that requires a new category that requires a new conceptual frame on the supply side so that buyers understand it. Yeah. But the, but like we think that, okay, I'm gonna go out and build something totally new and different. Mm-hmm. And then convince the world to want it flips the order. Yeah. It's, I'm observing customers who are trying to accomplish things, but their existing supply options do not fit I offer them something different that perhaps has some magical new technology that I'm leveraging for it such that those, so that when they see it, they compare it versus their existing options that aren't good enough. And they say, oh my God, this is so much better. And they rip it out of our hands.

Yeah. It's, um, Listening to that, the way that you frame that, it's like there's— you've written in the past, you've said in the past, like nobody wants demand to apply to them and they don't want pull to apply to them. And inventing a, you know, a new category like that happens, like new categories emerge, new technologies emerge. However, it's— this is maybe a way of saying like, yes, it still applies to you and you should understand the demand behind it rather than just thinking that supply will, it may unleash demand like you may, you know, it may be like the dam that breaks and but it does not create the demand that's behind it. And there is work that needs to be done in understanding that demand before overinvesting in supply.

And what you actually just brought up is something— it's a gripe I have with basically all marketers out there, which they're going to love. All 4 of them who listen to this are going to love this part. But there's, there's a bunch of marketers who focus on the category first, the category of product first. And, or they focus on, you know, there's like this whole thing about creating new categories and that stuff makes sense, but is downstream of demand. You have to understand demand first. And the problem is that like you can say all the research out there on, okay, but if you are If you own a category, you take X share of the, like, you, you know, your business is way better if you own a new category of things. And that is literally true, but it is downstream of demand existing and existing supply options being a bad fit for that demand, which requires a new category of thing emerging. Right. It just skips all of the relevant causality. Yeah. Yeah. This is my problem with like category creation. This is my problem with a lot of the positioning stuff out there. It just, it winds up with stuff that sounds right and makes sense, but doesn't take off.

Yeah. It could be used to explain in retrospect or to describe in retrospect, but it is, if you start from a, I want to create a new category, there's like, that's that's not how the world works. And I know, unfortunately.

Yeah. And again, I don't want any of this to apply to me. I want to create a new category. I like, I don't, I want to just run through kind of like a, kind of like a marketing exercise and have my startup take off. But I have to, we have to understand that demand exists out there. We have to observe it and where people are blocked. And bring technologies to bear and assemble them in a way that fits better than their existing options on the supply side.

Yeah, yeah. Love it. Let's jump into AI now. I'm going to maybe read just like one, one short sentence here, which brings us to AI. This is right as you're transitioning away from, you know, from the Henry Ford example. AI products are growing fast, not because there is demand for AI, but because buyers demand had bad options prior to AI. Bring us into, into AI world. What is, let's tease explicitly, tease apart supply and demand here.

Yeah. Yeah. Okay. So AI is on the supply side. It is a technology just like the automobile. It is not a thing that people are trying to accomplish in their lives. So just like the idea that nobody wanted an automobile, nobody wants AI. They're trying to accomplish things in their lives, which they would be trying to accomplish whether or not AI existed, but the existence of AI may enable them to accomplish things in better ways in their minds than their previous options. Enable them to. And so we have to understand that demand and supply split also is relevant here. Of course it's relevant here because if we think that buyers want AI, we're gonna miss entirely what's causing startups to take off. Yeah.

Why don't we, let's talk about that. What is, what are the mistakes that you see founders making when they misunderstand or they blur the lines between what is demand and, and, you know, desire for supply?

Play? Yeah. So basically you pitch AI as the, as the like first order thing.

What does that, what does that look like? Um, uh, yeah.

So like what, what will happen? So a very common example I see, I've seen probably like 10 examples of this where, uh, uh, startup says we are like AI enables new kinds of workflows. We are an AI horizontal workflows platform, which means we can do any kind of workflow. And this is novel because da da da da da da da, right? What that is pitching is kind of like a capability on the supply side. It is not pitching like unblocking on the demand side. But it's not, it's not even clear what's on the demand side there.

Yeah. Is there an example of positioning for demand? Like how would, how would you start? I don't know. I don't know if there's like a generic one, one that we could, we could bring up, but with that same technology positioned to resonate with demand rather than to lead with supply, like how does that, how does that look?

Yeah. I mean, I think, I think we can just go through some of these examples here. Like that might be the best place to start where it's like, why don't we start with like, so what, what I try to do is I try to show this in a couple of different examples. I have a long laundry list of ones I could also, that we could also go through. Yeah. Um, but like, I figured like why don't we hit the, yeah.

Before we hit the example, you write something very interesting about, um, the two things that AI does and how to think about it. You write, if AI is changing anything in buyers' minds, it is injecting one of two thoughts. I'd call the first one— I don't know, this might actually be the wrong way of characterizing it, Rob, but I think of the first one as like a better way. And then the next one is like now possible. The first is maybe there's a better way to do X now, you know, to do X being a random thing because of AI. And then the now possible, the second one, maybe why this, this thing I've always wanted to do but haven't been able to do is now possible because of AI. Let's talk for just maybe a moment about what you see from what's going on on the customer side, because I think there is curiosity about, about AI that how like how does that those two thoughts, a better way or a now possible, how does that relate to demand or how does that connect to supply? Yeah.

So it's like, you know, if I'm in a situation where my current supply does not fit my demand, so I'm doing something, let's say I'm doing something manually every single day. That's like tedious. Like let's say taking meeting notes. Right. Like I have just coping with the fact that that's the best fit supply that is available to me now.. And so I'm just gonna keep doing that. When AI comes around as this thing where it's like, you know, it's like, oh, maybe software can be, can do human things now. That opens my mind to the possibility that this kind of thing I've been coping with because it was the best thing available for the demand that I, that I have is the best available thing. Now my mind is open to, oh, maybe there's a new, a better way. No, that's example 1. Example 2 is, you know, maybe this demand that I've had with no supply that fit, right? Like is now possible. And so I've always wanted to build an awesome website. I've always wanted to build an app, but I'm non-technical. And so if, so maybe now I can. Maybe it's now, that thing is now possible. Like that's, there's like a, the conceptual frame of AI as, as basically like software that can do human things is opening, is like opening buyers' minds to possibilities. But those possibilities are things that were on their to-do list previously. They were thing, their demand was there. Yeah, yeah.

It's not, I want to use AI, I want to use more AI in my job. It's AI is, as you say, helping me to do something better or enabling me to do something that previously I couldn't. That's the perfect transition, actually. I'm glad you talked through that. That helps me better understand a couple of these case studies that we're about to hit. Why don't we walk through. Let's start with Jump, which is one we've talked about in the past. The context on Jump is, you know, that's, that's a startup you worked closely with and they do, or they started as— I think they've probably evolved somewhat since then, but as meeting notes for financial planners. What is the situation? Or AI-generated meeting notes for financial planners. What is going on with Jump and how does, uh, as an AI startup, how does, uh, how do supply and demand play into it?

Yeah, so, so you can look at Jump's story and you can see, wow, they have a beautiful product. They have amazing marketing. They have, right, like all, they have an insanely good team and they've been able to raise a ton of money. And so you can look at those things and say, oh, that's what caused them to take off. That is 0% of what caused them to take off. That is how they've resp— that's how they have very intelligently responded to demand that existed, that, that, that their AI product, their product that happens to use AI harnessed, right? And so what we have to do is we have to Look at Jump, this super fast-growing startup, and we'll do this for a couple others as well and say, okay, what was going on with their customers before Jump existed? And so I, I've created this, I think this is actually a really, really cool way to think about it now, which is let's just look at the financial advisor's calendar. Yeah. Of what are they doing minute by minute before Jump exists? What they're doing, you know, you, you imagine there's a client meeting that's an hour-long client meeting and for 45 minutes before and 45 minutes after or whatever, uh, they are taking notes and prepping and putting stuff into their CRM before and after every single client meeting. And this is legally, I think, or like regulatorily if that's a word, required for, for them to do that. So this is like non-negotiable. They are doing these things before and after client meetings. Now, that is a fact, right? They are, they are doing that. That is observable. What is not observable is do they want to be doing— does that, that is supply. What they are doing is their supply. They're doing it manually. What we don't know is what is their demand in that moment? And it turns out their demand in that moment was while they're taking these notes, while they're documenting the meetings, was like, I want to be spending the least amount of time doing this tedious work. The, the just observing the calendar doesn't tell you enough. Yeah. You have to connect the calendar to what's the real demand that the calendar is, and the difference between the fact that they are taking meeting notes and don't wanna be taking meeting notes, it doesn't, that doesn't fit is what created the situ— this, that's where demand or pull existed, right? Like they, they're doing this thing that's unavoidable and their existing options their existing options on the supply side aren't fitting, but they're just grinding through it every day. And that, that mismatch, it's, it, that is the, the, the like water against the dam, right? That's just pressing against this. And there's this force here that when Jump shows up and says, now AI can take that off of your plate. Hmm. That is what causes— that's the thing that causes customers to rip the product out of their hands. That's what causes them to grow so fast. That's what causes all of these other things downstream to be effective. But this is where causality starts. Yeah.

Let's, um, let's take it back to the Henry Ford, uh, one on this, or listening to you is making me think of that. So if we think of like the pre, pre-automobile and pre-AI world, in this case pre-automobile, it was the demand was I need to go from A to B and the supply was I have a horse or I can walk. Pre-AI or pre— yeah, yeah, pre-generative AI. What we had in this case was I have to take notes and the supply that they had available in that case was manually take notes and save in the folder or something, you know, whatever it is, however they're doing that to comply with the regulatory environment. Post now going to Henry Ford. Okay, automobile. Now you can go 5 times faster. You don't have to feed your car in the same way. You don't know whatever it is. And it— and so the buyer is ripping the car out of the— of Henry Ford's hands. In this case, it's The demand is— I, maybe this is a slight reframing. Rob, tell me how I'm wrong or if this is wrong. I think the demand is have notes that are created and then it's now it is a— this falls in the better way of doing that. Previously, I had to manually go through the suffering of writing those out and saving them and thinking about them. And now I can have those notes faster without the same manual effort. And so it's the better— it falls into your, your categorization of the better way of doing work enabled by— that happens to be enabled by AI. Yeah. Yeah.

I mean, that's— I think that's totally right. Like you would. And I think the really important thing to understand here is that there is like if you look at somebody's calendar, right, in the automobile example, you would either see their, I don't know, they didn't have Google Calendar back then, but right, like you just imagine someone's calendar and you just see a long stretch of sitting on a horse, right? And, or you see, or you, you, you see nothing, right? Because they didn't, you don't, you don't see the trips they didn't take because a horse was too annoying to take, right? Or, or whatever. That's interesting. And, and so, and so that's what you see. And by observing that, you know something, you know, the supply, like you kind of know the supply side. What you need to infer is what's on their to-do list in their mind. Right? Like, does that supply fit? And, and like, what could we offer that, that fits better? Yeah.

I, I, I love that. Thinking about what would a Google Calendar have looked like for, you know, George Washington and it's like sit on horse for very long time. Really long time. Okay, let's, uh, anything else on, on Jump that you want to hit, or do we want to get into everybody's favorite topic, SDRs?

Yeah, yeah, let's, let's jump to AI. I, I, um, I organized these 3 examples in a way to, to, uh, unlock new ideas in each one.

And so let's jump to SDRs. Sweet. Um, so SDRs, for, um, those that may not be familiar with the terminology, sales development rep. Um, so these are basically people are frequently— you write about this frequently— fairly junior employees, that their job is generate new business. You work with more of the AI SDR space. But Rob, can you, can you describe a little bit what is, what is that like? What is managing SDRs like? And then what's your assessment of how AI like plays into this?

Yeah. So like there's like many different terminologies. There's BDRs, there's SDRs. I'm not quite sure what the current hip technology is. What I'm talking about specifically are the people who try to do outbound to schedule new sales conversations, right? And there's— AI SDR is the closest, or SDR in general is like the closest thing I can say. And a lot of people are out there saying, hey, we— or maybe a year ago or whenever, we're talking about the AI SDR being like the new thing. And, and, um, there are a lot of AI SDR companies out there. Um, but like zooming out, right? Let's, okay. So why are these, why have these companies grown fast? And then, you know, like what's actually happening with them? I think is an interesting question. So, uh, but let's start on the demand side, right? We are trying to schedule meetings like via outbound. We're just trying to hit our outbound targets. We're trying to generate pipeline. Um, SDRs. Are a form of supply for that demand. Mm-hmm. And when you have SDRs, you spend a lot of time managing them because they are right, like they're generally people who are pretty much outta college, just outta college. It's their first job or, you know, close to their first job in a lot of cases. And so I don't know if you were this way, but I remember when I was just out of college in my first job, I was an idiot for like a long period of just doing really dumb things. And I had very patient managers who had to basically deal with the fact that I was creating zero or negative value for quite a while. And so that's just so like in general, managing people who are very junior is very difficult. And also outbound is really hard. So you have the combination of very hard thing to do, managing SDRs, very hard thing to do, outbound. Combine both of those and you see like managing SDRs is hard and generally sucks. Hmm. Now what I'll say is I, I actually really like working with SDRs, like It, you can, but the default is that it's a hard job to do.

Then the management of the SDRs. Oh, yes.

The management, being an SDR, everything in this realm is generally fairly difficult. Yeah. And so, and so what, like you wind up as a manager spending a bunch of time obviously doing management things, right? SDRs turn over pretty frequently. So you're always trying to hire new ones. It's hard to vet them. You get people and then you have to train them and then you have to kind of like performance manage. And then, you know, there are some people who are just pretending to make phone calls and they're not actually making phone calls and you have to track all the data. You have to do all like, there's all of this management work. And if you are managing an SDR and you're doing all of this management work, you can, you can imagine what that calendar looks like, all the things that are happening there. Now, for some people, they're just like, yeah, great. This is fine. For most people who are in that role, there is at least some of the time, the supply they're doing, the things they're doing in the moment, their calendar does not reflect what's on their to-do list. What's on their to-do list is I just want to hit these outbound targets and like the, the management Managing SDRs and all that, the kind of like grueling work of doing that. Hmm. Doesn't fit the, the demand I have. And so that, that difference between what's on my calendar and what's actually on my to-do list, what I actually am trying to accomplish, is where the idea of an AI SDR is so compelling. Because it's like hit your outbound targets without all of that management work. Yeah.

Yeah. It's, uh, and it's not, I want AI, um, I want AI to do outbound for me. It's right now it is very painful and, uh, expensive and annoying, uh, in many cases to manage human beings in this case. And if there is supply that is better than, hiring a bunch of 23-year-olds to, you know, do outbound calls and to, you know, watch over them while they're doing that, then I would pull that, uh, is what your kind of like assessment of that situation is.

Yeah. Yeah. Yeah. And it's, it's, let's like, yeah, let's get out of the, let's avoid the pain talk here, but let's, let's write, like, it's the, what I'm trying to accomplish and SDRs, or they, it kind of fits. But I'm coping. I'm doing a lot of coping and it doesn't really fit, right? Like I, a lot of that, just like with meeting notes, when I'm taking meeting notes, what I really want to be doing is I just want the meeting notes done. I don't want to be doing the tea. Like I want to do that with the least amount of my own effort. Same thing here. When I'm managing SDRs, when I'm hiring new ones, when I'm doing all this training, I'm just trying to hit my outbound, like hit the outbound targets and all of this work is stuff that I often don't want to be doing. And the difference between those two is where there's space for something new to be ripped out of, of, right, for me to rip out of your hands.

Yeah. Um, conscious of time, uh, do you want to hop into AI app builders?

First I want to, so first what I want to say is the, the difference here, like this is the, the next level of the topic I want to unlock, which is Um, uh, many people complain about AI SDRs that they're just spam cannons. They don't work. They don't personalize messages. Like, they're litany of complaints. Yeah. They can be right about every single complaint and they're wrong about what matters. Hmm. Right. Like, even if AI SDRs do not currently work, there is pressure against a dam here that will, when it is technologically feasible, if and when it is technologically feasible, this will, like, a product here will be ripped out of buyer's hand or out of the seller's hands, right? And so what matters is not, right, like, it, it, uh, the complaints can be true and irrelevant. Hmm. Would that—

is that the equivalent of the first cars broke down too often and they like, they didn't, you know, the tires didn't work. There was safety problems with it. Like, and it was like there was a— the supply was not fully developed. Right. Right.

Or like, or like you hear a bunch of stuff, like you hear about early, the early days of HubSpot and the product would just crash nonstop. And it like didn't matter. Yeah. And so here, right, what you'll see and hear about is that AI SDRs as they exist today have a massive churn problem. Yeah. Which because of all of these complaints and total, like that all totally makes sense, but there's still demand. There's still demand pressing against a wall. And if something can fit that demand, which is an if I literally don't know, I do not know if something can be built that is general purchase purpose that can fit kind of any, any kind of SDR situation. If that's the case, the demand is there and the market will rip that out of the seller's hands.

Yeah.

Um, all right. Love it. Love it. Yeah.

Yeah. Let's, uh, let's, uh, I'll just, uh, open the door. Hit it. Tell us, give us the context here.

So the interesting thing about, so what we've talked about so far are examples where you can look at somebody's calendar and watch what they are doing. And by looking at their calendar, watching what they're doing and kind of like inferring what's on their, what are, what are they really trying to accomplish? You can see, okay, what they're doing doesn't fit what they are trying to accomplish. This takes it the other direction, which is. Um, VibeCoding basically gives people who couldn't code the ability to kind of code. Um, and, and so if you looked at these buyers, their, their calendars before this, what you would, you would not see them building an app or a website. They literally couldn't. You wouldn't see that, but what you realize is that That was actually very high priority on their to-do list. They wanted to be doing that, but there was literally no supply that fit for them to be able to do that. And so, so that, that's the like difference here where previously you would see them. Yeah. Previously you'd see how people are spending their time and say, oh, that doesn't fit the to-do list in their brain very well. This other thing does. Oh yeah. They'll like, that causes them to rip out of their hands. This is the case of when you look at their calendar, see nothing. And this is why we have to get back to the to-do list in people's brains, what demand really is.

Yeah. So in, in this case, um, like vibe coding platforms like Lovable, what they do is they come in and, uh, a small business owner, something like that, like wants to have an app that they feel like they would make their product better. Their alternative was so expensive, or the supply was so expensive, or so complicated, or so inaccessible, um, that they maybe they didn't even know where to start with it, or, uh, or they weren't willing to make the investment. And now it's, uh, you know, going back to your two examples, it's a better way or now possible. Now it's the now possible for me to have this thing that previously wasn't, uh, yeah, wasn't available. Yeah. Yeah.

And just like the thing, the thing on all of these, if we zoom out, is that there's this to-do list in buyers' brains, right? And that's what's going to cause startups to take off. AI happens to enable either thing like new capability, new things that I couldn't have done previously, but were on my things I really wanted to do. Yeah. Or it's going to enable new things that fit the things I was already doing that didn't fit what was on my to-do list.

Yeah. Yeah. Um, and that, you know, getting that maybe just like real quick, and this is probably over, over hit in this episode, but the, the important thing here for me at least is the demand is supply agnostic. Supply might be wrong. You actually, you call this out with, uh, with the lovable example as well. You know, you write here, you'll also hear that all the complaints from those who think that vibe coding doesn't work, they might be right, but it doesn't matter. The demand is here. And so it's an observation of there are critiques of the supply, which is vibe coding doesn't work, which is different from a statement that the demand for that type of supply doesn't exist. And so, you know, as we're thinking about it.

Yeah, yeah, yeah. So like demand exists. And that demand will make vibe coding work if that is technically possible ever. Right. That will pull vibe coding that works into existence.

Yeah. Yeah. Um, well, I hope that, I hope this was helpful for the listener. Um, and some piece of any final, what, what should, let's make this maybe practical, any recommendations for, uh, you know, founders that are listening to this, what should they do with this, this post? Yeah. Yeah. Okay.

So we kind of. First, focus on who, who do you think your customers are? And look at their calendar, like go observe what they are doing and try to figure out what's actually on their to-do list and where these two things don't really match. That, that's where demand, like that's where pull is found and you test that. Right? Like that's where you start. AI happens to be an awesome technology that can now unblock a lot of these things. Hmm. Start by calendar and to-do list, prototype something, AKA like a sales prototype. So just a slide or something to pitch a supply. That would fit that, what you think is the demand and see what happens. If you're right, calendar and to-do list don't really match up, they should pull. Hmm. And it's like, like that's how, that's what causes everything downstream to work. That's what's causing these startups to grow so fast.

Yeah. Love it. Um, Any last thoughts, Rob, before we wrap this one up? No. All right, cool. Uh, well folks, uh, leave comments. We've got, uh, maybe one last thing on the mailbag. Uh, Philip Heidecker, forgive me if I'm butchering your last name. Um, you left an interesting, uh, mailbag about pull and the relationship with pricing, onboarding, et cetera. Um, that's one that's on Rob's mind. We're not hitting it directly here, but it's, uh, you know, stay tuned. It's a, it's a, it's a really good question and something Rob's been thinking about. Um, and other folks, drop a, drop a comment if you've got something you want, uh, Rob to, to discuss, either on YouTube or on Rob's Substack, uh, or Spotify. Um, otherwise we will catch everybody next week.